The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states

TL;DR

This study classifies 87 galaxy clusters into relaxed, intermediate, and disturbed states using optical and X-ray data, employing PCA to analyze six proxies and confirming the classifications through galaxy and gas distribution comparisons.

Contribution

Introduces a PCA-based method to classify galaxy clusters' dynamical states using multiple proxies, enabling robust categorization for future studies.

Findings

Successful segregation of clusters into three dynamical states

Classification consistent with galaxy and gas distribution data

Statistically distinguishable dynamical categories

Abstract

While the influence of galaxy clusters on galaxy evolution is relatively well-understood, the impact of the dynamical states of these clusters is less clear. This paper series explores how the dynamical state of galaxy clusters affects their galaxy populations' physical and morphological properties. The primary aim of this first paper is to evaluate the dynamical state of 87 massive ($M_{500} \geq 1.5 \times 10^{14} M_{\odot}$) galaxy clusters at low redshifts ($0.10 \leq z \leq 0.35$). This will allow us to have a well-characterized sample for analyzing physical and morphological properties in our next work. We employ six dynamical state proxies utilizing optical and X-ray imaging data. Principal Component Analysis (PCA) is applied to integrate these proxies effectively, allowing for robust classification of galaxy clusters into relaxed, intermediate, and disturbed states based on their dynamical characteristics. The methodology successfully segregates the galaxy clusters into the three dynamical states. Examination of the galaxy distributions in optical wavelengths and gas distributions in X-ray further confirms the consistency of these classifications. The clusters' dynamical states are statistically distinguishable, providing a clear categorization for further analysis.